Motivated by the social and environmental challenges resulting from the COVID‐19 pandemic, this research examines the influence of the “big five” personality traits; extroversion, agreeableness, openness, conscientiousness, and neuroticism on sustainable social responsibility with a mediating role of bricolage. We collected empirical evidence from 245 family‐owned SMEs. The results indicate that the personality traits do not directly influence sustainable social responsibility, although the traits (except extroversion) influence bricolage. Moreover, we found that open, conscious, and agreeable personalities indirectly contribute to sustainable (...) social responsibility, with bricolage as a mediator. Our findings encourage enterprises to focus on those personality traits during crises (especially COVID‐19) that empower people to effectively manage existing resources (e.g., bricolage) and protect their stakeholders. Family‐owned SMEs need to assign resource utilization tasks to family members having personalities of openness, conscientiousness, and neuroticism because these kinds of people have high capacities for bricolage. (shrink)

Computer vision and human–computer interaction are essential in many technological fields. Researchers in CV are particularly interested in real-time object detection techniques, which have a wide range of applications, including inspection systems. In this study, we design and implement real-time object detection and recognition systems using the single-shoot detector algorithm and deep learning techniques with pre-trained models. The system can detect static and moving objects in real-time and recognize the object’s class. The primary goals of this research were to investigate (...) and develop a real-time object detection system that employs deep learning and neural systems for real-time object detection and recognition. In addition, we evaluated the free available, pre-trained models with the SSD algorithm on various types of datasets to determine which models have high accuracy and speed when detecting an object. Moreover, the system is required to be operational on reasonable equipment. We tried and evaluated several deep learning structures and techniques during the coding procedure and developed and proposed a highly accurate and efficient object detection system. This system utilizes freely available datasets such as MS Common Objects in Context, PASCAL VOC, and Kitti. We evaluated our system’s accuracy using various metrics such as precision and recall. The proposed system achieved a high accuracy of 97% while detecting and recognizing real-time objects. (shrink)

The present study was conducted in Quetta district Balochistan province so as to determine the perception of the respondents about causes and consequences of child labor in Balochistan province. The sample size was 100 family units selected by using the simple random sampling. Somehow of the respondents fall in the age categories of 41 to 50 years, followed by 30% of the family units who were in the age categories of 50 and above years. More than half 52% of the (...) respondents were illiterates and the other of the respondents had primary level of education. The result is further expressed that the other 20% of the male respondents were of the view that the retail trade, cycling repairing and carpet business important child labor route respectively. While 20% of the female respondents revealed that they are cycling repairing and carpet business important child labor route respectively at Quetta district. Children are the assets of any nation without their contribution in the developmental process can be null and void, therefore it should be recommended that government must take stern action against the child labor at grass-root level to eliminate the child labor in the community or society. (shrink)